Mendelian randomization (MR) is considered to overcome the bias of observational studies, but there is no current meta-analysis of MR studies on rheumatoid arthritis (RA). The purpose of this study was to summarize the relationship between potential pathogenic factors and RA risk based on existing MR studies. PubMed, Web of Science, and Embase were searched for MR studies on influencing factors in relation to RA up to October 2022. Meta-analyses of MR studies assessing correlations between various potential pathogenic factors and RA were conducted. Random-effect and fixed-effect models were used to synthesize the odds ratios of various pathogenic factors and RA. The quality of the study was assessed using the Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization (STROBE-MR) guidelines.Aims
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Osteoarthritis (OA) is a common degenerative joint disease characterized by chronic inflammatory articular cartilage degradation. Long noncoding RNAs (lncRNAs) have been previously indicated to play an important role in inflammation-related diseases. Herein, the current study set out to explore the involvement of lncRNA H19 in OA. Firstly, OA mouse models and interleukin (IL)-1β-induced mouse chondrocytes were established. Expression patterns of IL-38 were determined in the synovial fluid and cartilage tissues from OA patients. Furthermore, the targeting relationship between lncRNA H19, tumour protein p53 (TP53), and IL-38 was determined by means of dual-luciferase reporter gene, chromatin immunoprecipitation, and RNA immunoprecipitation assays. Subsequent to gain- and loss-of-function assays, the levels of cartilage damage and proinflammatory factors were further detected using safranin O-fast green staining and enzyme-linked immunosorbent assay (ELISA) in vivo, respectively, while chondrocyte apoptosis was measured using Terminal deoxynucleotidyl transferase dUTP Nick-End Labeling (TUNEL) in vitro.Aims
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Rheumatoid arthritis (RA) is a systematic autoimmune disorder, characterized by synovial inflammation, bone and cartilage destruction, and disease involvement in multiple organs. Although numerous drugs are employed in RA treatment, some respond little and suffer from severe side effects. This study aimed to screen the candidate therapeutic targets and promising drugs in a novel method. We developed a module-based and cumulatively scoring approach that is a deeper-layer application of weighted gene co-expression network (WGCNA) and connectivity map (CMap) based on the high-throughput datasets.Aims
Methods